Merge K sorted linked list

In this video, we will discuss several approaches to merge K sorted linked lists into a single sorted list. The first method is a simple approach where we merge the lists one by one. Starting with an empty result list, we merge each linked list into the result using the standard merge algorithm for two sorted lists. This approach has a time complexity of O(n * k * k), where n is the length of each list and k is the number of lists, and uses O(1) space.

The second approach improves this by selecting the smallest node from all the current head nodes and adding it to the result list. By doing this iteratively, we eventually merge all the lists. This method also has a time complexity of O(n * k * k) and uses O(1) space. The third approach, using a min heap, is more efficient for unevenly sized lists. It reduces the time complexity to O(n * k * log k) by efficiently finding the minimum element across all lists. Lastly, the divide and conquer approach splits the lists into two halves recursively, merging them pair by pair, which is similar to merge sort. This method works best when the lists are of equal size and has a time complexity of O(n * k * log k). Watch the video to learn the details of these approaches and how to merge K sorted linked lists efficiently.

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